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In an age of ubiquitous computing when we all have high-bandwidth video streaming capabilities in our pockets, the fact that the humble GIF continues to thrive is remarkable. But its success is testament to the 30-year-old file format’s continued support and its ability to convey information (and entertain) without requiring huge processing power.
Indeed, GIFs continue to be used for many purposes, which is why Google has launched the Data Gif Maker, a tool aimed at helping journalists and storytellers convey information visually through simple animations.
“Data visualizations are an essential storytelling tool in journalism, and though they are often intricate, they don’t have to be complex,” said Simon Rogers, data editor at the Google News Lab, in a blog post. “In fact, with the growth of mobile devices as a primary method of consuming news, data visualizations can be simple images formatted for the device they appear on.”
The Data GIF Maker is pretty simple to use, though it is also fairly narrow in scope. It’s basically designed to help people show how two competing “things” compare to each other in terms of popularity, from sales of a particular product to the frequency with which two items appear in search engines. It requires the user to manually enter the information and then download the GIF.
The advent of the internet and big data has given rise to a number of businesses that aim to help people make sense of the deluge of information at their disposal in order to tell meaningful stories. For example, Latvian infographics and data visualization company Infogram offers a slick WYSIWYG editor that converts users’ data into infographics that can be published or embedded anywhere. It was acquired by Prezi earlier this month.
Other companies are making moves to monetize GIFs. Last month, Tenor launched a real-time analytics tool designed to educate marketers about using GIFs.
Google’s GIF effort has limited ambitions for now, but it could be turbocharged in the future to enable GIFs with far greater detail and multiple data points.
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